It conveniently doesn't mention the hardest part: conflicts.
If you just drop a conflicting edit then it's a stretch to call your app "offline". Yes, it "works" but who wants to use an application to at drops you edits?
If you just drop a conflicting edit then it's a stretch to call your app "offline". Yes, it "works" but who wants to use an application to at drops you edits?
Beyond that, you get into complex territory but maybe we've all been overthinking the problem space.
I may at an earlier part of my career, when I knew far less about building robust software, have stumbled into such an experience.
Proceeds to do millions of transactions a day.
The challenge is interpreting what that tree structure should mean.
If you can, let a user decide how to resolve the conflict.
- User logs in, they have a “conflict inbox” of things that need to be resolved.
- Two coworkers make conflicting edits, maybe the manager gets a notification in their conflict inbox and they decide
What you are describing is just the beginning of conflict handling. The consequences for bad handling are dire: data loss. If conflict handling and resolving was easy (hint: it's not), the article would have mentioned it.
Let’s take git as an example. If we both push changes to our branch, there’s no problem. We have a git repo with different branches. For a single record, this is even simpler, just an append-only table with a foreign key to the prior state.
If someone reviews a PR and finds a merge conflict, it gets handled. Maybe one wins, both get rejected, or both get accepted (a fork). But there’s no requirement that data be discarded.
But automating it seems impossible in all circumstances since it depends on the human intent.
1. Do you store the tree structure for every table in your app? If you have 20 tables that could be edited offline, do you re-implement it for each table, or try to have a generic implementation? 2. Do you design all your tables around the tree structure, or do you just store it in addition to your "normal" tables? 3. Every piece of code that modifies one of these tables need to do it via the tree structure - if you update your tables directly from any place it could effectively cause conflicts. 4. Do you build separate UI to resolve conflicts for every table? 5. Do you query and cache the tree structure on the device, or does it have to be online to resolve conflicts? 6. Do you expose the tree structure via external APIs, or keep it internal?
I find that "last-write-wins" is sufficient for a large percentage of cases, and much simpler to implement. Or in some cases, just doing conflict detection is sufficient (notify the user that the data has changed between loading and saving, and they need to re-apply their edits).
If you do need conflict resolution on a large scale (many different tables), I'd recommend using data structures designed for that. CRDTs is one example - while it is typically used for automatic conflict resolution, it often stores enough data to allow manual resolution if desired.
https://github.com/gerdemb/SQLiteChangesetSync
The library works at the database-level and stores databases modifications as binary change sets in a separate table that models a graph similar to a git repository. Capturing modifications is as simple as wrapping the transaction with a handler provided by the library. The graph of database modifications is stored locally on each device, but can easily by synced with an online repository.
The library detects conflicts, and provides a handler to the application for conflict resolution.
https://github.com/gerdemb/SQLiteChangesetSync
As you noted, detecting conflicts is easy, but handling them is not.
For most products, there isnt a one-size-fits-all answer to how to handle conflicts.